osundiranay Goto Github PK
Name: Ayoade J.
Type: User
Company: BitwisePathway
Bio: I am a full stack programmer and an AI enthusiast.
Location: Nigeria.
Blog: bipnov.com
Name: Ayoade J.
Type: User
Company: BitwisePathway
Bio: I am a full stack programmer and an AI enthusiast.
Location: Nigeria.
Blog: bipnov.com
100+ Python challenging programming exercises
Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy! We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning: Programming with Python NumPy with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations Machine Learning with SciKit Learn, including: Linear Regression K Nearest Neighbors K Means Clustering Decision Trees Random Forests Natural Language Processing Neural Nets and Deep Learning Support Vector Machines and much, much more! Enroll in the course and become a data scientist today! Wat zijn de vereisten? Some programming experience Admin permissions to download files Wat leer ik in deze cursus? Use Python for Data Science and Machine Learning Use Spark for Big Data Analysis Implement Machine Learning Algorithms Learn to use NumPy for Numerical Data Learn to use Pandas for Data Analysis Learn to use Matplotlib for Python Plotting Learn to use Seaborn for statistical plots Use Plotly for interactive dynamic visualizations Use SciKit-Learn for Machine Learning Tasks K-Means Clustering Logistic Regression Linear Regression Random Forest and Decision Trees Natural Language Processing and Spam Filters Neural Networks Support Vector Machines Wie is het doelpubliek? This course is meant for people with at least some programming experience
Python tutorials in both Jupyter Notebook and youtube format.
Exercise Files for Statistical Analysis in Data Science Using Python
Distribution (mostly continuous) estimation with Pytorch (MLE, MAP, REINFORCE, GAN, etc) notebooks for self learning.
R-Deep-Learning-Essentials-Second-Edition, Published by Packt
Providing script-files of R that is convenient and help implement statistical analyses easily and efficiently. Upload informative templates for both statistical analysis and data-cleansing. All script-files and resources I used for lectures can also be found on my web-site. Stuffs are free avairable, please use it. Have fun.
The code for the book 《R programming with applications to financial quantitive analysis》
Teaching material for elementary R programming lecture
:heavy_check_mark: BioStat mode for R Commander (Rcmdr): improved functions, menus, and buttons (R package)
In the folder, I followed Arthur Juliani's github and redid his tutorial about Reinforce Learning
Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence—from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it’s gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP.
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Simple reinforcement learning programs, inspired from https://simoninithomas.github.io/deep-rl-course/#syllabus
A Dashboard for a restaurant to create its core database.
Using some reinforcement learning algorithms (DQN, A2C, MCTS, REINFORCE, Qlearning) to solve Mountain Car, CartPol, and Breakout-v0 Problems with Gym and Tensorflow
Free and open source no-code application builder
Eggua Schisto Viz
The Simplest Blog Ever
Slightly less crappy PHP static site generator
In this Python ML project, I will use the libraries librosa, soundfile, and sklearn (among others) to build a model using an MLPClassifier. This will be able to recognize emotion from sound files. We will load the data, extract features from it, then split the dataset into training and testing sets. Then, we’ll initialize an MLPClassifier and train the model. Finally, we’ll calculate the accuracy of our model.
SQL - Hacker Rank and Stanford SQL Lab exercise solutions
SQL Zoo Exercise Solutions and University Course Material Queries
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.